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--- |
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license: cc |
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language: |
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- ve |
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- tn |
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- sot |
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- nso |
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metrics: |
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- perplexity |
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library_name: transformers |
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tags: |
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- tshivenda |
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- sotho |
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- south africa |
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- low-resource |
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- bantu |
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- xlm-roberta |
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widget: |
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- text: Rabulasi wa <mask> u khou bvelela nga u lima |
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- text: >- |
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Vhana vhane vha kha ḓi bva u bebwa vha kha khombo ya u <mask> nga |
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Listeriosis |
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--- |
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# Zabantu - Tshivenda & Sotho family |
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This is a variant of [Zabantu](https://huggingface.co/dsfsi/zabantu-bantu-250m) pre-trained on a multilingual dataset of Tshivenda(ven) and Sotho family(Northern Sotho, Southern Sotho, Setswana) sentences on a |
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transformer network with 170 million traininable parameters. |
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# Usage Example(s) |
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```python |
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from transformers import pipeline |
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# Initialize the pipeline for masked language model |
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unmasker = pipeline('fill-mask', model='dsfsi/zabantu-sot-ven-170m') |
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sample_sentences = ["Rabulasi wa <mask> u khou bvelela nga u lima", |
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"Vhana vhane vha kha ḓi bva u bebwa vha kha khombo ya u <mask> nga Listeriosis"] |
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# Perform the fill-mask task |
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results = unmasker(sentence) |
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# Display the results |
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for result in results: |
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print(f"Predicted word: {result['token_str']} - Score: {result['score']}") |
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print(f"Full sentence: {result['sequence']}\n") |
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print("=" * 80) |
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``` |
